Balancing nitrate acquisition strategies in symbiotic legumes.

Legumes manage both symbiotic (indirect) and non-symbiotic (direct) nitrogen acquisition pathways. Understanding and optimising the direct pathway for nitrate uptake will support greater legume growth and seed yields. Legumes have multiple pathways to acquire reduced nitrogen to grow and set seed.

Allocation of Resources to Cyanogenic Glucosides Does Not Incur a Growth Sacrifice in (L.) Moench.

In plants, the production of secondary metabolites is considered to be at the expense of primary growth. Sorghum produces a cyanogenic glycoside (dhurrin) that is believed to act as its chemical defence. Studies have shown that acyanogenic plants are smaller in size compared to the wildtype.

Stratified Diabetes Mellitus Prevalence for the Northwestern Nigerian States, a Data Mining Approach.

An accurate classification for diabetes mellitus (DBM) allows for the adequate treatment and handling of its menace, particularly in developing countries like Nigeria. This study proposes data mining techniques for the classification and identification of the prevalence of diagnosed diabetes cases, stratified by age, gender, diabetic conditions and residential area in the northwestern states of Nigeria, based on the real-life data derived from government-owned hospitals in the region. A K-mean assessment was used to cluster the instances, after 12 iterations the instances classified out of 3022: 2662 (88.

Principal Component Analysis of Categorized Polytomous Variable-Based Classification of Diabetes and Other Chronic Diseases.

A chronic disease diabetes mellitus is assuming pestilence proportion worldwide. Therefore prevalence is important in all aspects. Researchers have introduced various methods, but still, the improvement is a need for classification techniques.

Data mining process for predicting diabetes mellitus based model about other chronic diseases: a case study of the northwestern part of Nigeria.

To predict diabetes mellitus model data mining (DM) based approaches on the dataset collected from the seven northwestern states of Nigeria. Data were collected from both primary and secondary sources through questionnaires and verbal interviews from patients with diabetic mellitus and other chronic diseases. Some hospital data were also used from the records of patients involved in this work.

A hybrid Forecast Cost Benefit Classification of diabetes mellitus prevalence based on epidemiological study on Real-life patient's data.

The increasing ratio of diabetes is found risky across the planet. Therefore, the diagnosis is important in population with extreme risk of diabetes. In this study, a decision-making classifier (J48) is applied over a data-mining platform (Weka) to measure accuracy and linear regression on classification results to forecast cost/benefit ratio in diabetes mellitus patients along with prevalence.

A Euclidean Group Assessment on Semi-Supervised Clustering for Healthcare Clinical Implications Based on Real-Life Data.

The grouping of clusters is an important task to perform for the initial stage of clinical implication and diagnosis of a disease. The researchers performed evaluation work on instance distributions and cluster groups for epidemic classification, based on manual data extracted from various repositories, in order to evaluate Euclidean points. This study was carried out on Weka (3.

Molecular characterization of a new synthetic cry2ab gene in Nicotiana tabacum.

A newly-synthesized cry2Ab gene was characterized in Nicotiana tabacum, before its further transformation in cotton. Synthetic cry2Ab gene was cloned in pGreen0029 and its expression was transiently analyzed at mRNA level through agroinfiltration in tobacco. The mRNA of cry2Ab was detected after 72 h agroinfiltration through PCR using total plant RNA.

Development of broad-spectrum insect-resistant tobacco by expression of synthetic cry1Ac and cry2Ab genes.

Efficacy of two newly synthesized cry1Ac and cry2Ab genes was checked in tobacco before their expression in cotton. Both genes were artificially synthesized and codon optimized with respect to cotton-preferred codon usage. These genes were cloned in a plant expression vector and then transformed into tobacco.